Manzorro, R., Xu, Y., Vincent, J., Rivera, R., Matteson, D., & Crozier, P. (2022). Exploring Blob Detection to Determine Atomic Column Positions and Intensities in Time-Resolved TEM Images with Ultra-Low Signal-to-Noise. Microscopy and Microanalysis, 1-14. doi:10.1017/S1431927622000356.
Xu, Y., Düker, M. C., & Matteson, D. S. (2021). Testing Simultaneous Diagonalizability. arXiv preprint arXiv:2101.07776.
Goolsby, C., Losey, J., Xu, Y., Düker, M. C., Sherman, M. G., Matteson, D. S., & Moradi, M. (2021). Addressing the Embeddability Problem in Transition Rate Estimation. bioRxiv preprint bioRxiv:707919.
Thomas, A. M., Crozier, P. A., Xu, Y., & Matteson, D. S. (2022). Detection and hypothesis testing of features in extremely noisy image series using topological data analysis, with applications to nanoparticle videos. arXiv preprint arXiv:2209.13584.
Contributed & Poster. Joint Statistical Meeting (JSM), Business and Economic Statistics Section, Speed Session. July 2019. Denver, CO.
Poster. Cornell Celebration of Statistics and Data Science, Poster Session. Sept 2019. Ithaca, NY.
Contributed. UPSTAT 2021 Conference, Parallel Session, Bronze Medal Presenter. Apr 2021. (Virtual) Rochester, NY.
Contributed. The 37th SIDIM, Data Science in Science Minisymposia, Parallel Session. Feb 2022. (Virtual) Puerto Rico.
Contributed. 2022 INFORMS Annual Meeting, Science-Integrated Statistical Learning Section, Technical Session. Oct 2022. Indianapolis, IN.
Poster. 2022 IEEE Western New York Image and Signal Processing Workshop (WNYISPW), Poster Session, Best Student Poster Award. Nov 2022. (Hybrid) Rochester, NY.
Prof. Roberto Rivera: propose and adapt hidden Markov models to dynamically cluster nanoparticle atomic structural configurations.
Prof. Peter A. Crozier: adapt blob detection algorithm to extract locations and intensities of atomic columns.
Prof. Mahmoud Moradi: refine the estimators of Markov chain transition rate matrices from transition probability matrices.